Date Published: February 1, 2019
Publisher: Public Library of Science
Author(s): Alexander T. Limkakeng, Ricardo Henao, Deepak Voora, Thomas O’Connell, Michelle Griffin, Ephraim L. Tsalik, Svati Shah, Christopher W. Woods, Geoffrey S. Ginsburg, Giuseppina Novo.
The heart is a metabolically active organ, and plasma acylcarnitines are associated with long-term risk for myocardial infarction. We hypothesized that myocardial ischemia from cardiac stress testing will produce dynamic changes in acylcarnitine and amino acid levels compared to levels seen in matched control patients with normal stress tests.
We analyzed targeted metabolomic profiles in a pilot study of 20 case patients with inducible ischemia on stress testing from an existing prospectively collected repository of 357 consecutive patients presenting with symptoms of Acute Coronary Syndrome (ACS) in an Emergency Department (ED) observation unit between November 2012 and September 2014. We selected 20 controls matched on age, sex, and body-mass index (BMI). A peripheral blood sample was drawn <1 hour before stress testing and 2 hours after stress testing on each patient. We assayed 60 select acylcarnitines and amino acids by tandem mass spectrometry (MS/MS) using a Quattro Micro instrument (Waters Corporation, Milford, MA). Metabolite values were log transformed for skew. We then performed bivariable analysis for stress test outcome and both individual timepoint metabolite concentrations and stress-delta metabolite ratios (T2/T0). False discovery rates (FDR) were calculated for 60 metabolites while controlling for age, sex, and BMI. We built multivariable regularized linear models to predict stress test outcome from metabolomics data at times 0, 2 hours, and log ratio between these two. We used leave-one-out cross-validation to estimate the performance characteristics of the model. Nine of our 20 case subjects were male. Cases’ average age was 55.8, with an average BMI 29.5. Bivariable analysis identified 5 metabolites associated with positive stress tests (FDR < 0.2): alanine, C14:1-OH, C16:1, C18:2, C20:4. The multivariable regularized linear models built on T0 and T2 had Area Under the ROC Curve (AUC-ROC) between 0.5 and 0.55, however, the log(T2/T0) model yielded 0.625 AUC, with 65% sensitivity and 60% specificity. The top metabolites selected by the model were: Ala, Arg, C12-OH/C10-DC, C14:1-OH, C16:1, C18:2, C18:1, C20:4 and C18:1-DC. Stress-delta metabolite analysis of patients undergoing stress testing is feasible. Future studies with a larger sample size are warranted.
Acute Coronary Syndrome (ACS) remains the leading cause of morbidity and mortality for Americans, accounting for 1 out of every 3 deaths . Each year, over 6 million people are rushed to emergency departments (ED) with ACS symptoms and many more receive testing as outpatients . Cardiac biomarkers and provocative stress testing are the mainstays of ACS risk assessment but have limitations [3–6].
Table 1 shows the demographic and clinical characteristics of chosen patients, and each individual’s characteristics are shown in S2 Table. The prevalence of known coronary artery disease and of coronary artery disease risk factors was low. Nine of our 20 case subjects were male. Cases’ median age was 55.5 and median BMI 30.1.
There is considerable interest in blood-borne markers of myocardial ischemia and early myocardial injury. Metabolomic profiles have been proposed as one approach for identifying these entities, both through systems biology approaches and as a means to identify traditional biomarker candidates. In this study, we matched patients with ischemia on exercise stress testing to patients without ischemia to compare metabolomic profile changes from baseline to 2 hours after their stress test. We have preliminarily found 5 metabolites that appear to change in concentration differently in patients with myocardial ischemia compared to those without on standard stress testing. We consider this to be hypothesis-generating work for further exploration and validation, but demonstrates the feasibility of the data collection and statistical analysis.
We studied whether there were dynamic changes in a large number of selected metabolites between patients with myocardial ischemia on stress testing compared to matched normal controls, preliminarily identifying 5 metabolites that appear to change differentially. It is unclear whether these results can contribute additional information above standard clinical evaluation for myocardial ischemia. Delta-metabolite concentrations may offer more discriminative value than static single-timepoint metabolite measurement. This model of metabolomic exploration warrants further investigation.